Taxonomic analysis with percent
Preparation
Paths and libraries setting
# Load main packages, paths and custom functions
source("../../../source/main_packages.R")
source("../../../source/functions.R")
# Load supplementary packages
packages <- c("RColorBrewer", "ggpubr", "cowplot")
invisible(lapply(packages, require, character.only = TRUE))Load phyloseq object after decontam
ps.filter <- readRDS("../../../../output/1_MED/1D/1D_MED_phyloseq_decontam.rds")
df <- psmelt(ps.filter)
colnames(df)[colnames(df) %in% "sample_Species"] <- "Species.x"Setting plot display
# new names for Genus
new_names_genus <- c("Wolbachia",
"Asaia",
"Legionella",
"Elizabethkingia",
"Chryseobacterium",
"Erwinia",
"Morganella",
"Pseudomonas",
"Delftia",
"Methylobacterium-Methylorubrum",
"Serratia",
"Coetzeea",
"NA"
)
# col for Genus
col_genus <- c("Wolbachia"="#FEB24C",
"Asaia"="#10E015",
"Legionella"="#DE3F23",
"Elizabethkingia"="#66A7ED",
"Chryseobacterium"="#F899FF",
"Erwinia"="#FFE352",
"Morganella"="#F5E4D3",
"Pseudomonas"="#DBF5F0",
"Delftia"="#C7C5B7",
"Methylobacterium-Methylorubrum"="blue",
"Serratia"="#B136F5",
"Coetzeea"="red",
"NA"="grey")
# param for plot
guide_italics <- guides(fill = guide_legend(label.theme = element_text(size = 10, face = "italic", colour = "Black", angle = 0)))
# labels
make.italic <- function(x) as.expression(lapply(x, function(y) bquote(italic(.(y)))))
labels = c("Wolbachia"=make.italic("Wolbachia"),
"Asaia"=make.italic("Asaia"),
"Legionella"=make.italic("Legionella"),
"Elizabethkingia"=make.italic("Elizabethkingia"),
"Chryseobacterium"=make.italic("Chryseobacterium"),
"Erwinia"=make.italic("Erwinia"),
"Morganella"=make.italic("Morganella"),
"Pseudomonas"=make.italic("Pseudomonas"),
"Delftia"=make.italic("Delftia"),
"Methylobacterium-Methylorubrum"=make.italic("Methylobacterium-Methylorubrum"),
"Serratia"=make.italic("Serratia"),
"Coetzeea"=make.italic("Coetzeea"),
"NA"
)Taxonomic % plots
Culex pipiens
Whole
df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
pipiens1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.pipiens1
Whole - Bosc
df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Field - Bosc",] %>%
group_by(Strain, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
pipiens2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="Field - Bosc", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.pipiens2
Whole - Camping Europe
df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Field - Camping Europe",] %>%
group_by(Strain, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
pipiens3 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="Field - Camping Europe", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.pipiens3
Whole - Lavar
df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Laboratory - Lavar",] %>%
group_by(Strain, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
pipiens4 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="Laboratory - Lavar", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.pipiens4
Ovary
df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Ovary",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
pipiens5 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Ovary")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.pipiens5
Groups
# Plot
p_pipiens <- plot_grid(pipiens1+ theme(legend.position="none"),
pipiens2+ theme(legend.position="none"),
pipiens3+ theme(legend.position="none"),
pipiens4+ theme(legend.position="none"),
pipiens5+ theme(legend.position="none", plot.margin = unit(c(0.17,-1,1.2,0), "cm")),
ncol = 5,
nrow = 2)Culex quinquefasciatus
Whole
df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
quinque1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.quinque1
Whole - Guadeloupe
df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole" & df$Strain=="Field - Guadeloupe",] %>%
group_by(Strain, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
quinque2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="Field - Guadeloupe", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.quinque2
Whole - Slab TC
df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole" & df$Strain=="Laboratory - Slab TC (Wolbachia -)",] %>%
group_by(Strain, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
quinque3 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="Laboratory - Slab TC (Wolbachia -)", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.quinque3
Ovary
df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Ovary",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
quinque4 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Ovary")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.quinque4
Groups
# Plot
p_quinque <- plot_grid(quinque1+ theme(legend.position="none"),
quinque2+ theme(legend.position="none"),
quinque3+ theme(legend.position="none"),
quinque4+ theme(legend.position="none", plot.margin = unit(c(0.17,0,1.2,0), "cm")),
plot.new(),
ncol = 5,
nrow = 2)
p_quinque
Aedes aegyti
Whole
df_plot <- df[df$Species.x=="Aedes aegypti" & df$Organ=="Whole",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
aedes1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Aedes aegytpi - Whole")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.aedes1
Ovary
df_plot <- df[df$Species.x=="Aedes aegypti" & df$Organ=="Ovary",] %>%
group_by(Species.x, Genus) %>%
summarise(read_sum = sum(Abundance))## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]
df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)
df_plot <- droplevels(df_plot)
aedes2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
geom_bar(position = "dodge", stat = "identity")+
scale_fill_manual(values = col_genus)+
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
ggtitle("") +
guide_italics+
theme(legend.title = element_text(size = 18), legend.position="bottom")+
theme(panel.spacing=unit(0,"lines"),
strip.background=element_rect(color="grey30", fill="grey90"),
panel.border=element_rect(color="grey90"),
plot.title=element_text(size=10),
axis.ticks.x=element_blank()) +
geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
scale_y_continuous(breaks=seq(0,105, by=10))+
scale_x_discrete(labels = labels)+
ylim(0,100)+
labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Aedes aegytpi - Ovary")+
theme(plot.tag.position = "topright",
plot.subtitle=element_text(size=10, face="italic", color="black"))## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.aedes2
Groups
# Plot
p_aedes <- plot_grid(aedes1+ theme(legend.position="none"),
aedes2+ theme(legend.position="none", plot.margin = unit(c(0.17,0,1.2,0), "cm")),
plot.new(),
plot.new(),
plot.new(),
ncol = 5,
nrow = 2)
Plot with all
p_global <- plot_grid(pipiens1+ theme(legend.position="none"),
pipiens2+ theme(legend.position="none"),
pipiens3+ theme(legend.position="none"),
pipiens4+ theme(legend.position="none"),
pipiens5+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")),
quinque1+ theme(legend.position="none"),
quinque2+ theme(legend.position="none"),
quinque3+ theme(legend.position="none"),
quinque4+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")),
plot.new(),
aedes1+ theme(legend.position="none"),
#aedes2+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")),
plot.new(),
plot.new(),
plot.new(),
nrow=3,
ncol=5
)
p_global
Save plots
tiff("../../../../output/1_MED/1E/1Ef_MED_taxonomic_percent.tiff", units="in", width=25, height=20, res=300)
p_global
dev.off()## quartz_off_screen
## 2tiff("../../../../output/1_MED/1E/1Ef_MED_taxonomic_percent.png", units="in", width=25, height=20, res=300)
p_global
dev.off()## quartz_off_screen
## 2Session info
sessionInfo()## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] cowplot_1.1.0 ggpubr_0.4.0 RColorBrewer_1.1-2 forcats_0.5.0
## [5] stringr_1.4.0 dplyr_1.0.2 purrr_0.3.4 readr_1.4.0
## [9] tidyr_1.1.2 tibble_3.0.4 tidyverse_1.3.0 ggplot2_3.3.2
## [13] phyloseq_1.30.0
##
## loaded via a namespace (and not attached):
## [1] nlme_3.1-149 fs_1.5.0 lubridate_1.7.9
## [4] httr_1.4.2 tools_3.6.3 backports_1.1.10
## [7] bslib_0.2.4 R6_2.4.1 vegan_2.5-6
## [10] DBI_1.1.0 BiocGenerics_0.32.0 mgcv_1.8-33
## [13] colorspace_2.0-0 permute_0.9-5 ade4_1.7-15
## [16] withr_2.3.0 tidyselect_1.1.0 curl_4.3
## [19] compiler_3.6.3 cli_2.1.0 rvest_0.3.6
## [22] Biobase_2.46.0 xml2_1.3.2 labeling_0.4.2
## [25] bookdown_0.22 sass_0.3.1 scales_1.1.1
## [28] digest_0.6.26 foreign_0.8-75 rmarkdown_2.7
## [31] rio_0.5.16 XVector_0.26.0 pkgconfig_2.0.3
## [34] htmltools_0.5.1.1 dbplyr_1.4.4 rlang_0.4.10
## [37] readxl_1.3.1 rstudioapi_0.11 farver_2.0.3
## [40] jquerylib_0.1.3 generics_0.0.2 jsonlite_1.7.1
## [43] zip_2.1.1 car_3.0-10 magrittr_1.5
## [46] biomformat_1.14.0 Matrix_1.2-18 fansi_0.4.1
## [49] Rcpp_1.0.5 munsell_0.5.0 S4Vectors_0.24.4
## [52] Rhdf5lib_1.8.0 abind_1.4-5 ape_5.4-1
## [55] lifecycle_0.2.0 stringi_1.5.3 yaml_2.2.1
## [58] carData_3.0-4 MASS_7.3-53 zlibbioc_1.32.0
## [61] rhdf5_2.30.1 plyr_1.8.6 grid_3.6.3
## [64] blob_1.2.1 parallel_3.6.3 crayon_1.3.4
## [67] lattice_0.20-41 Biostrings_2.54.0 haven_2.3.1
## [70] splines_3.6.3 multtest_2.42.0 hms_0.5.3
## [73] ps_1.4.0 knitr_1.30 pillar_1.4.6
## [76] igraph_1.2.6 ggsignif_0.6.0 reshape2_1.4.4
## [79] codetools_0.2-16 stats4_3.6.3 reprex_0.3.0
## [82] glue_1.4.2 evaluate_0.14 data.table_1.13.2
## [85] modelr_0.1.8 vctrs_0.3.4 rmdformats_1.0.2
## [88] foreach_1.5.1 cellranger_1.1.0 gtable_0.3.0
## [91] assertthat_0.2.1 openxlsx_4.2.3 xfun_0.22
## [94] broom_0.7.2 rstatix_0.6.0 survival_3.2-7
## [97] iterators_1.0.13 IRanges_2.20.2 cluster_2.1.0
## [100] ellipsis_0.3.1